Book chapter N°18 of "Cooperative and Graph Signal Processing"; Academic Press, ISBN: 978-0128136775
Advances in theory, integration techniques and standardization have led to huge progress in wireless technologies. Despite successes with past and current (5G) research, new paradigms leading to greater spectral efficiencies and intelligent network organizations will be in great demand to absorb the continuous growth in mobile data. With few exceptions such as ad-hoc topologies, classical wireless design places the radio device under the tight control of the network. Pure network-centric, centralized, designs, such as optical cloud-supported ones raise cost and security concerns and do not fit all deployment scenarios. Also they make the network increasingly dependent on a large amount of signaling and measurements taken at the network's edge, that must be communicated in real time to a centralized network processing node, which is not always possible or desirable. To circumvent this problem, an alternative (or complementary) system design approach can be imagined in which devices' local computational capabilities are leveraged to a greater extent. Such nodes can for instance be Transmitters (TXs) trying to coordinate in view of suppressing mutual interference or more generally cooperate in order to maximize a network-level performance. While such wireless nodes are cooperative, they typically act in the face of uncertain (noisy) system/channel state information affecting their own measurements as well as the measurements at other nodes. In addition to measurement noise, decision making is also hindered by limited information exchange capabilities between the nodes. Such impairments prevent perfect coordination and call for robust algorithms.
Deriving the optimal transmission decisions (so-called Team Decisional (TD) methods) at each node under such decentralized information scenario is a difficult problem with interesting connections to fundamental information theoretic, control, signal processing and learning problems. In this chapter we provide a general formulation for TD methods for device cooperation in wireless networks. We introduce relevant decentralized information models and classes of decision making solutions. We illustrate these various approaches through the prism of one specific example, namely the problem of decentralized MIMO beamforming (precoding) in wireless networks.
© Academic Press. Personal use of this material is permitted. The definitive version of this paper was published in Book chapter N°18 of "Cooperative and Graph Signal Processing"; Academic Press, ISBN: 978-0128136775 and is available at : https://doi.org/10.1016/B978-0-12-813677-5.00018-3